class_docstr: Head which outputs a Mixture of Gaussians Distribution.
docstr: Create an mixture of Gaussian actor head.
  
  Args:
    num_dimensions: dimensionality of the output distribution. Each dimension
      is going to be an independent 1d GMM model.
    num_components: number of mixture components.
    init_scale: the initial scale for the Gaussian mixture components.
    num_mixtures: deprecated argument which overwrites num_components.
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code: def __init__(
      self,
      num_dimensions: int,
      num_components: int = 5,
      init_scale: Optional[float] = None,
      num_mixtures: Optional[int] = None,
  ):
      """Create an mixture of Gaussian actor head.
  
      Args:
        num_dimensions: dimensionality of the output distribution. Each dimension
          is going to be an independent 1d GMM model.
        num_components: number of mixture components.
        init_scale: the initial scale for the Gaussian mixture components.
        num_mixtures: deprecated argument which overwrites num_components.
      """
      if num_mixtures is not None:
          logging.warning(
              """the num_mixtures parameter has been deprecated; use
                      num_components instead; the value of num_components is being
                      ignored"""
          )
          num_components = num_mixtures
      super().__init__(
          num_dimensions=num_dimensions,
          num_components=num_components,
          multivariate=False,
          init_scale=init_scale,
          name="UnivariateGaussianMixture",
      )
  
imports: import types
  from typing import Optional, Union
  from absl import logging
  from acme.tf.networks import distributions
  import numpy
  import sonnet
  import tensorflow
  import tensorflow_probability
label_desc: Use image node_id 1 to create a new UnivariateGaussianMixture object from inherited base classes: GaussianMixture with example: obj = UnivariateGaussianMixture(num_dimensions, num_components, init_scale, num_mixtures)